scRNA-agent / By Lab Agent Works

Single-cell RNA-seq analysis, directed by you.

scRNA-agent helps biologists analyze their own data with local R/Python tools and specialized AI-assisted guidance, from quality control and annotation to figures and reports.

View Windows availabilityWindows · Coming soon

Built for biologists

Less distance between a question and an analysis.

Routine analysis can demand substantial computational expertise. scRNA-agent helps bridge that gap.

Interact with an agent that uses project context, executes local R/Python tools, and tracks outputs as your analysis develops.

It supports iterative biological exploration without replacing scientific judgment. Complex study design, unusual datasets, and challenging interpretation may still require expert bioinformatics.

The analysis framework

Guidance from data intake to interpretation.

01

Start with the data

  1. Data intake
  2. Quality control
  3. Filtering
02

Assess & prepare

  1. Doublet detection
  2. Ambient RNA handling
  3. Dimensionality reduction
03

Resolve the biology

  1. Batch / integration assessment
  2. Clustering
  3. Annotation
04

Explore & communicate

  1. Differential analysis
  2. Pathway analysis
  3. Figures and reports

An adaptable framework, not a fixed pipeline. The steps and methods depend on the dataset and biological question.

The system concept

A local workspace. A connected Core.

Local tools perform the computation. Your own model access supports reasoning and execution. The protected Core provides maintained scientific guidance and product services.

On your computerLOCAL WORKSPACE
01

Your scientific data

Raw matrices & processed inputs

02

scRNA-agent workspace

Your question, context & decisions

03

R / Python analysis

Local scientific computation

04

Project outputs

Figures, tables, reports & provenance

Raw matrices stay on your computer. Scientific computation runs locally.

YOUR MODEL ACCESS

Your own AI provider supports reasoning and execution. Prompts and shared project context may leave your computer and are subject to that provider’s policies.

An example interaction

Ask in the language of your research.

Researcher
“Compare the annotated T cells and myeloid cells using Hallmark GSEA and generate the plots.”
scRNA-agent / Illustrative workflow
  1. Prepare the comparison and clarify the analysis design.
  2. Acquire supported reference resources when needed.
  3. Run the analysis in the local scientific environment.
  4. Generate figures and reports for researcher review.
  5. Preserve project provenance and analysis artifacts.

An example of the intended interaction, not a scientific result. Method choices require review in the context of the study.

What you keep

Outputs that stay with your project.

Figures & tables

Visual summaries and tabular results for review and further exploration.

figures/ · tables/

Analysis & provenance

Analysis artifacts, parameters, and records that keep the work traceable.

artifacts/ · provenance/

Summaries & reports

Scientist-facing summaries alongside technical reports for deeper inspection.

summaries/ · reports/

Illustrative output categories. Contents depend on the analysis performed.

Product capabilities

Made for careful, iterative work.

01

Guided analysis workflow

Move from a biological question to a structured analysis, with decisions you can review.

02

Local R / Python execution

Run scientific tools in local environments, close to your data.

03

Project-aware AI assistance

Work with an agent that uses your project context to support the next step.

04

Reference-resource handling

Acquire supported reference resources automatically when an analysis needs them.

05

Reproducible figures and reports

Keep generated figures and reports connected to the analysis that produced them.

06

Versioned analysis guidance

Use maintained guidance with versions that can be traced across your work.

07

Protected scientific skills

Access specialized analysis skills through the protected Core service.

08

Traceable project outputs

Retain analysis artifacts, parameters, and provenance in your project.

09

Local-first data handling

Keep raw matrices and project files under your control.

10

Maintained workflow improvements

Benefit from developer-maintained guidance and reusable analysis experience.

Data handling

Keep raw scientific data local.

The Core does not need your raw dataset. Your model provider is a separate connection, with its own policies for shared context.

Read the privacy model

Common questions

Before you get started.

Who is scRNA-agent for?

Primarily biologists who want to work directly with their single-cell RNA-seq data, with structured computational guidance. Complex study design and interpretation may still benefit from expert bioinformatics support.

Does it replace scientific judgment?

No. Researchers review analysis choices, assess quality, and interpret findings. AI assistance and workflow guidance do not guarantee scientific correctness.

Where does my data go?

Raw matrices and large scientific datasets stay in your local workspace. The protected Core supplies guidance and product services without needing the raw dataset. Your model provider is a separate service; review what context you share and its data policies.

Do I need my own AI access?

Yes. scRNA-agent uses your own model authentication for AI reasoning and execution. Provider availability, terms, and charges are separate from Lab Agent Works membership.

What happens when membership ends?

Existing local projects and results remain available. Active membership is required for new protected scientific analysis.

Can I download it now?

The Windows installer is coming soon. The download page will carry the signed installer and verified release details when available.

Your next biological question

Closer to your data.
Further in your research.

Meet scRNA-agent, the first tool from Lab Agent Works.

View scRNA-agent availability